Multi-threat maritime detection system

ABSTRACT

A system adapted to collect security parameters from a shipping container while a container lifting mechanism is lifting and moving said container, comprising: a mount adapted to attach at least one sensor to a container lifting mechanism, wherein the at least one sensor is adapted to capture at least one sensor parameter associated with a shipping container while the container lifting mechanism lifts said shipping container; a network interface adapted to receive over a network at least one manifest parameter associated with the shipping container; at least one hardware processor adapted to execute code for detecting a mismatch between data deduced from an analysis of the at least one sensor parameter and the at least one manifest parameter, and outputting a signal indicative of said mismatch.

RELATED APPLICATIONS

This application is a National Phase of PCT Patent Application No.PCT/IL2017/051248 having International filing date of Nov. 15, 2017,which claims the benefit of priority under 35 USC § 119(e) of U.S.Provisional Patent Application No. 62/422,289 filed on Nov. 15, 2016.The contents of the above applications are all incorporated by referenceas if fully set forth herein in their entirety.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to a systemfor inspecting shipping containers and, more specifically, but notexclusively, to sensors attached to a container lifting mechanism thatcollects security parameters from a container while the containerlifting mechanism is moving the container.

150-200 million containers pass between shipping container seaports eachyear. Due to cost and logistical issues, the percentage of containersinspected, physically or by technological means, is estimated at 2-3% ofthe total shipped containers.

The contents of the containers may comprise explosives, narcotics,weapons, chemicals, dirty bombs, people, counterfeit money, and more.One method of smuggling contraband in a container is an illegal use oflegitimate customers (Trojan horse.

Most of the inspections are based on scanning technologies using X-ray,GAMA, sucking the air out of the container for a long period of time andtesting it by technological detectors, and/or physical examination asthe opening of the container which requires the presence of customspersonnel.

In order to optimize the inspections mentioned above, there are a numberof companies and programs that build a profile of containers bygathering information on the shipper and the recipient. The profile isdesigned to allow focusing inspection resources on the defined suspectedcontainers. The problem with this method is that while profiledinspections are more likely than random inspections to locate securityrisks, it doesn't increase the number of inspections carried out. Inaddition, it is possible to bypass the physical or technologicalinspection by forging a profile.

SUMMARY OF THE INVENTION

According to an aspect of some embodiments of the present inventionthere is provided a system adapted to collect security parameters from ashipping container while a container lifting mechanism is lifting andmoving the container, comprising: a mount adapted to attach at least onesensor to a container lifting mechanism, wherein the at least one sensoris adapted to capture at least one sensor parameter associated with ashipping container while the container lifting mechanism lifts theshipping container, a network interface adapted to receive over anetwork at least one manifest parameter associated with the shippingcontainer, at least one hardware processor adapted to execute code fordetecting a mismatch between data deduced from an analysis of the atleast one sensor parameter and the at least one manifest parameter, andoutputting a signal indicative of the mismatch.

Optionally, the hardware processor is further adapted to execute codefor correlating the mismatch with a security category, wherein thecorrelation is calculated by at least one member of a list of techniquescomprising statistical classification, correlation, linear regression,logistic regression, linear discriminant analysis, non-linearregression, and comparing an expected range of values with the detectedmismatch.

Optionally, the hardware processor is further adapted to execute codefor a database management system (DBMS) adapted to storing andinstructing transmitting of the at least one sensor parameter.

Optionally, the at least one sensor comprises at least one member of agroup consisting of weight sensors, length sensors, image sensors,barcode sensors, video recorders, gamma ray sensors, explosives sensors,radiation sensors, and hazardous material sensors, and wherein the atleast one sensor parameter comprises parameters captured by acorresponding the at least one sensor.

Optionally, the analysis comprises at least one member of a list ofanalysis techniques comprising calculating at least one discrepancybetween a value of the at least one sensor parameter and an expectedrange of values, calculating at least one discrepancy between a value ofthe at least one manifest parameter and an expected range of values,image processing, video content analysis (VCA), and optical characterrecognition (OCR).

Optionally, the mismatch comprises a discrepancy between the deduceddata and the at least one manifest parameter greater than an expectedvalue.

Optionally, the at least one manifest parameter comprises at least oneof a list of parameters associated with the shipping containerconsisting of a subset of the at least one sensor parameter, shippinghistory, owner of the container, an identification number, owner of acontents of the container, a manifest of contents, identity ofreceivers, identity of senders, a shipping company responsible fordelivery between any two points in the shipping history, and any otherparameters associated with the shipping container.

Optionally, the hardware processor is further adapted to execute codefor detecting a mismatch between data deduced from the analysis of theat least one manifest parameter and the analysis of the at least onesensor parameter.

Optionally, the hardware processor is further adapted to execute codefor detecting a mismatch between data deduced from the analysis of aplurality of the at least one manifest parameters.

Optionally, the hardware processor is further adapted to execute codefor detecting a mismatch between data deduced from the analysis of aplurality of the at least one sensor parameters.

Optionally, the mount comprises a connecting arm wherein a distal end isattached to the at least one sensor, and a proximal end is attached tothe container lifting mechanism.

Optionally, the mount provides at least one degree of freedom betweenthe at least one sensor and the container lifting mechanism.

Optionally, the mount comprises an electro-mechanical mechanism whichautomatically positions the sensor in proximity to at least one optimalposition for detecting at least one the sensor parameter.

Optionally, mount automatically moves the sensor through a range ofpositions and orientations relative to the container lifting mechanism.

Optionally, the mount is controlled remotely by a user utilizing acontroller interface.

According to an aspect of some embodiments of the present inventionthere is provided a system for collecting, storing, and distributingsecurity parameters associated with a shipping container comprising: atleast one computing processor comprising: a network interface adapted toreceive over a network at least one sensor parameter from at least onesensor mounted on at least one container lifting mechanism and at leastone manifest parameter associated with the shipping container, at leastone hardware processor adapted to execute code instructions, the codeinstructions comprising a database management system (DBMS), and theDBMS adapted to receive queries for data associated with the shippingcontainer, and to respond with the at least one sensor parameter.

More optionally, the at least one sensor comprises at least one memberof a group consisting of weight sensors, length sensors, image sensors,barcode sensors, video recorders, gamma ray sensors, explosives sensors,radiation sensors, and hazardous material sensors, and wherein the atleast one sensor parameter comprises parameters captured by acorresponding the at least one sensor.

More optionally, the at least one manifest parameter comprises at leastone of a list of parameters associated with the shipping containerconsisting of a subset of the at least one sensor parameter, shippinghistory, owner of the container, an identification number, owner of acontents of the container, a manifest of contents, identity ofreceivers, identity of senders, a shipping company responsible fordelivery between any two points in the shipping history, and any otherparameters associated with the shipping container.

More optionally, the code instruction for detecting a mismatch betweendata deduced from an analysis of the at least one sensor parameter andan analysis of the at least one manifest parameter.

According to an aspect of some embodiments of the present inventionthere is provided a method for collecting security parameters from ashipping container while a container lifting mechanism is lifting andmoving the container, comprising: mounting at least one sensor to acontainer lifting mechanism, wherein the at least one sensor is adaptedto capture at least one sensor parameter associated with a shippingcontainer while the container lifting mechanism lifts the shippingcontainer, receiving the at least one sensor parameter, receiving over anetwork at least one manifest parameter associated with the shippingcontainer, detecting a mismatch between data deduced from an analysis ofthe at least one sensor parameter and the at least one manifestparameter, and outputting a signal indicative of the mismatch.

More optionally, the at least one sensor comprising at least one memberof a group consisting of weight sensors, length sensors, image sensors,barcode sensors, video recorders, gamma ray sensors, explosives sensors,radiation sensors, and hazardous material sensors, wherein the at leastone sensor parameter comprising parameters captured by a correspondingthe sensor.

More optionally, the at least one manifest parameter comprises at leastone of a list of parameters associated with the shipping containerconsisting of a subset of the at least one sensor parameter, shippinghistory, ownership, an identification number, a manifest of contents,identity of receivers, identity of senders, a shipping companyresponsible for delivery between any two points in the shipping history,and any other parameters associated with the shipping container.

More optionally, the analysis of the at least one sensor parametercomprises at least one member of a list of analysis techniquescomprising comparing values of sensor parameters with an expected rangeof values of sensor parameters, image processing, video content analysis(VCA), and optical character recognition (OCR).

More optionally, further comprising detecting the mismatch between datadeduced from the analysis of the at least one manifest parameter and theanalysis of the at least one sensor parameter.

More optionally, further comprising detecting the mismatch between datadeduced from the analysis of a plurality of the at least one manifestparameters.

More optionally, further comprising detecting the mismatch between datadeduced from the analysis of a plurality of the at least one sensorparameters.

More optionally, a security category is correlated with the mismatch,wherein the correlation is calculated by at least one member of a listof techniques comprising statistical classification, correlation, linearregression, logistic regression, linear discriminant analysis,non-linear regression, and comparing an expected range of values withthe detected mismatch.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention. In this regard, thedescription taken with the drawings makes apparent to those skilled inthe art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1 is a flowchart of a process for inspecting containers based onsensor and documented data while being moved by a container liftingmechanism, according to some embodiments of the present invention;

FIG. 2 is a schematic illustration of an exemplary system for inspectingcontainers based on sensor and documented data while being moved by acontainer lifting mechanism, according to some embodiments of thepresent invention;

FIG. 3 is a schematic illustration of information flow for generatingalarms in another embodiment of the system for inspecting containers inFIG. 1 , according to some embodiments of the present invention;

FIG. 4 is a schematic illustration of another embodiment of the systemshown in FIG. 2 , according to some embodiments of the presentinvention;

FIG. 5 is a schematic illustration of a system for collecting, storing,and distributing parameters and metadata associated with shippingcontainers, according to some embodiments of the present invention; and

FIG. 6 is a schematic illustration of a system for collecting, storing,and distributing parameters and metadata associated with shippingcontainers and connected to external tracking sources, according to someembodiments of the present invention.

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to a systemfor inspecting shipping containers and, more specifically, but notexclusively, to sensors attached to a container lifting mechanism thatcollects security parameters from a container while the liftingmechanism is moving the container.

The time it takes to inspect the shipping containers and the logisticsof moving the container into and out of an inspection area is a problemfor shipping companies and port operators. Container ports are designedto efficiently move containers from shore to ship and/or vice versa, andadding an inspection to this process increases both economic andlogistical overhead. The present invention, in some embodiments thereof,comprises a system for inspecting a container during the time that acontainer lifting mechanism is moving the container from ship to shoreand vice versa based on sensor and documented data.

The present invention, in some embodiments, is a system comprising oneor more sensors attachable by a mount to a container lifting mechanism,a hardware (HW) processing platform, and networking interfaces.

The container lifting mechanism may be for example any type of crane,lifting mechanism, forklift and/or any other mechanism adapted to liftand/or move a shipping container.

A container may be a shipping container, an International StandardsOrganization (ISO) container, an intermodal container, and/or any othercontainer that may be moved by a shipping container lifting mechanism.

The sensor(s) are adapted to collect a plurality of security relatedparameters from a container as the container is being moved by thelifting mechanism and transmitting the parameters to the hardwareprocessing platform.

The hardware processing platform is adapted to receiving parametersassociated with the container from the sensors and/or from networkresources such as a shipping container database, to calculate report(s)from the received parameters that are descriptive of possible securityand/or legal issues associated with the container, and to transmitspecific report(s) to specific personnel, for example a reportcomprising detection of hazardous levels of radiation may be transmittedto a security officer, and a report describing taxable cargo within thecontainer may be transmitted to a customs official.

The sensors may include image sensors, hazardous materials sensors,weight sensors, and the like, and may be attached to the liftingmechanism by an adjustable arm to allow collecting a plurality ofparameters from a plurality of orientations relative to the container.

The hardware processing platform may further comprises a database (DB)and/or a management system (DBMS), for example stored in a non-volatilecomputer memory and/or stored remotely on a service cloud, that isadapted to receive, store, and/or transmit the parameters collected fromthe sensors, the calculated reports, and/or the parameters received fromnetwork resources.

By utilizing the time while a lifting mechanism performs loading andunloading of containers from a ship to a dock, and vice versa, thecurrent invention, in some embodiments, enables the inspection of everycontainer that passes through a shipping port without introducing delaysor other logistical impediments to the port operations. By integrating avariety of types of sensors, the system is capable of inspecting a widerange of security related parameters. By connecting multiple systems toa networked DBSM, the collected parameters may be added to historicaldata from the container and other containers around the world togenerate a database of container parameters that may be used to enhancesecurity status calculation capabilities.

According to some embodiments of the present invention, container datacollected in different ports from different lifting devices whilecontainers are lifted allows mapping the location of containers in everygiven moment and to detect suspicious loading and unloading patterns,for example containers having an origin which does not match ageographical transport route and/or unexpected changes such as weightchanges, color changes, and/or security risking flaws.

Before explaining one or more embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings and/or the Examples. The invention iscapable of other embodiments or of being practiced or carried out invarious ways.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network.

The computer readable program instructions may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider). In some embodiments, electronic circuitry including, forexample, programmable logic circuitry, field-programmable gate arrays(FPGA), or programmable logic arrays (PLA) may execute the computerreadable program instructions by utilizing state information of thecomputer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Reference is now made to FIG. 1 , which is a flowchart schematicallyrepresenting a process 100 for calculating and transmitting a securityassessment for a shipping container as the container is being moved by acontainer lifting mechanism, according to some embodiments of thepresent invention.

The security assessment(s) may be calculated, for example by thehardware processor, from a variety of inputs comprising values ofparameters received from sensors mounted on the container liftingmechanism, from historical data received from network resources, and/orfrom input by user(s). User input may be received for example via aninterface to the hardware processing platform and/or from networkresources.

Parameters received from the sensors which are installed on thecontainer lifting mechanism are referred to herein as sensor parameters.Parameters from shipping certificates and/or other historical parametersmay be received from network resources such as servers and other remoteComputing Systems, and are referred to herein as manifest parameters

The security assessment may comprise report(s), alarm(s), and/orsecurity category(s). User input parameters may define the content andtarget network address(s) of each security assessment according to anintended recipient. Each security assessment may be transmitted to theintended recipient, for example by a network interface.

Reports may comprise a subset of the received parameter values and/orcalculations based on the received parameter values. The calculationallows detecting a mismatch between sensor parameter(s) and manifestparameter(s) and/or detecting suspicious patterns or routes based on amismatch between current parameter(s) and historical parameter(s).Examples of mismatches are described below.

Alarms may comprise a type of report, for example a report that requiresthe recipient to perform an activity. For example, a security officerwho receives an alarm descriptive of detection of a high level ofhazardous material may be required to quarantine the associatedcontainer.

Security categories may comprise a numeral and/or a descriptive termrepresentative of an assessment of a potential risk that the associatedcontainer may contain some form of contraband, for example explosivesand/or counterfeit money, and/or one or more of the parametersassociated with the container is incorrect, for example the ownership ofthe container may different than the parameter received from a networkresource. For example, possible security categories may be numerals onethrough ten, where one represents zero risk, and ascending numeralsrepresent ascending level of risk.

The security category may be calculated, for example by the hardwareprocessing platform executing a correlation algorithm. The correlationalgorithm may be for example a statistical classifier and/or a linearregression, which detects combinations of received parameters and/ormismatches between received parameters that are correlated with aspecific security category.

Examples of mismatches include the following: a mismatch between valuesof a manifest parameter and a corresponding sensor parameter, forexample a mismatch in the weight values or color values of thecontainer. A mismatch may be detected based on logic rules applied tospecific values of a specific group of manifest parameters, for examplethe combination of manifest parameter values of Libya as the port oforigin, Liberia as the registered nationality of shipping company, andRussia as the country of the destination port may be detected as amismatch due to historical security issues with this combination ofvalues of manifest parameters. A mismatch may be detected betweenmultiple historical manifest values representing the same containercharacteristic, for example a mismatch value manifest parametersrepresenting the color of the container as recorded at origin anddestination shipping ports, for instance by the image sensors attachedto a container lifting mechanism at each location.

Reference is now made to FIG. 2 , a schematic illustration of exemplaryLifting Unit Device (LUD) 200 for collecting values of parameters from acontainer while the container is moved by a monitored container liftingmechanism, such as a crane, and optionally classifying the containerbased on correlations between the gathered sensor parameters andmanifest parameters received from network resources, according to someembodiments of the present invention.

LUD 200 comprises a hardware processing platform comprisingcommunications interface input/output (I/O) 220, LUD HW processor 221,and storage 208, and one or more mounts attaching one or more sensors210 to a container lifting mechanism 212.

Sensor 210 collects sensor parameters from container 213 as container213 is lifted and/or moved by container lifting mechanism 212. Sensors210 may transmit an output signal representative of the collectedparameters I/O 220 directly and/or via network 230. I/O 220 communicatesthe signals to LUD HW processor 221.

I/O 220, LUD HW processor 221, and storage 208 may comprise for examplea server, a desktop computer, an embedded computing system, anindustrial computer, a ruggedized computer, a laptop, a cloud computer,a private cloud, a public cloud, a hybrid cloud, and/or any other typeof computing system. Optionally, LUD 200 comprises a virtual machine(VM) in place of I/O 220, LUD HW processor 221, storage 208.

Process 100 may be executed by LUD HW Processor 221 executing code fromone or more software modules in storage 208, for example ParameterAnalyzer module 201, Reports Generator module 202, Classifier Calculatormodule 203, Reports Transmitter module 204, and/or a DBMS module. TheDBMS module may comprise code instructions for a database, a DBMS, adistributed database, and/or a distributed database management system(DDBMS).

Optionally, Process 100 may be executed remotely on a VM, a cloudcomputing platform, a Central Unit 500 as described below, and/or a PortUnit 550 as described below.

LUD HW processor 221 is adapted to receive and/or fetch sensor outputssuch as signals from I/O 220 for executing the software modules. LUD HWprocessor 221 is adapted to fetch records, user input as describedbelow, and/or other data from memory 208 as input(s) to executing thesoftware modules.

Wherein a software module refers to a plurality of program instructionsstored in a non-transitory medium such as storage 208 and executed by aprocessor such as processor 221.

LUD HW Processor 221 may comprise one or more processors, HWprocessor(s), multi-core processor(s), and/or any other type of coreprocessing unit (CPU). Storage 208 may include one or morenon-transitory persistent storage devices, for example, a hard drive, aFlash array and the like.

I/O 220 may be adapted to receiving to storage 208 sensor parameters,manifest parameters, reports, alarms and/or security categories. I/O 220may be adapted to transmitting sensor parameters, manifest parameters,reports, alarms and/or security categories.

Optionally, I/O 220 may comprise one or more input interfaces, forexample a keyboard, a soft keyboard, a touch screen, a graphical userinterface (GUI), a voice to text system, and/or any other data inputinterface. I/O 220 may comprise one or more output interfaces, forexample a screen, a touch screen, video display, and/or any other visualdisplay device.

Optionally, I/O 220 may comprise a network interface card (NIC), awireless router, and/or any other type of network interface adapted tocommunicating with network 230.

Network 230 may be any type of data network, for example, a local areanetwork (LAN), a fiber optic network, an Ethernet LAN, a fiber opticLAN, a digital subscriber line (DSL), a wireless LAN (WLAN), a wide areanetwork (WAN), a broadband connection, an Internet connection using anInternet Service Provider (ISP) and/or any other type of computernetwork. Network 230 may employ any type of data networking protocols,including transport control protocol and/or internet protocol (TCP/IP),user datagram protocol (UDP), Bluetooth, Bluetooth low energy (BLE),802.11 compliant wireless local area network (WLAN), and/or any otherwired or wireless LAN or WAN protocol.

Optionally, the one or more sensors 210 may be include weight sensor(s),length sensor(s), image sensor(s), barcode sensor(s), video recorder(s),gamma ray sensor(s), explosives sensor(s), radiation sensor(s), audiblelevel sensor(s), hazardous material sensor(s) and/or any other type ofsensor(s) that may collect security parameters from a container 213.Each sensor 210 generates an output signal corresponding to one or moreparameter associated with container 213.

The output signal may be an analog signal, a digital signal, and/or anetworking protocol signal adapted to communicating with I/O 220 and/ornetwork 230.

Optionally, one or more to sensors 210 may be connected to one or morenetwork interface device(s) which receives signals from one or moresensors 210 and transmits digital parameters to network 230 and/or toLUD HW Processor 221. The network interface device may comprise ananalog to digital converter, a digital repeater, a digital data formatconverter, and/or any other device for receiving sensor signals and/ortransmitting the digital parameters representative of the signals over adigital network. For example, sensor 210 may transmit signals on aUniversal Serial Bus (USB) to the network interface device which mayconvert the protocol from USB data to Ethernet (IEEE 802.3). The networkinterface device may support all networking protocols that are supportedby network 113 described below.

Optionally, the network interface device may be integrated within sensor210, wherein the sensor parameters are transmitted to network 113 and/orto I/O 220.

Optionally, one or more sensor 210 may time stamp corresponding outputsignals. The time stamps may be integrated into the signals sensors 210output, as described above, and stored in a computer record associatedwith the container, as described below. The time stamp may comprise botha time and a date.

Optionally, one or more sensors 210 are adapted to store a computer datafile comprising digital parameters representative of the sensor outputsover a period of time, and are adapted to transmit the computer datafile to storage 208, for example via network 230.

The values of the sensor parameters may be representative of for examplelength and/or weight of container 213, image files of container 213, anidentification number, video files, and range bound parameters, forexample a level of radiation, hazardous materials, and/or explosives andthe like.

Optionally, sensor 210 is attached to mount 211 which is attached tocontainer lifting mechanism 212. Mount 211 may comprise one or morerigid segment attachable at one end to sensor 210 and attachable atanother end to container lifting mechanism 212.

Optionally, mount 211 comprises a connecting mechanism that allowsmultiple degrees of freedom for sensor 210 relative to container 213,allowing positioning sensor 210 in a variety of locations and/ororientations relative to container 213. The connecting mechanism maycomprise one or more joints, ball joints, hinges, friction hinges, swinghinges, universal joints, constant velocity (CV) joints, and/or anyother form of connecting mechanism that allows multiple degrees offreedom.

Optionally, mount 211 comprises multiple rigid segments, each segmentattached to an adjoining segment with a connecting mechanism asdescribed above.

Optionally, mount 211 comprises an electro-mechanical mechanism forpositioning attached sensor 210 in a desired position relative tocontainer 213. The electro-mechanical mechanism may be controllable by aremote user control interface and/or by a computerized automatic controlmechanism.

Optionally, the computerized automatic control mechanism automaticallypositions sensor 210 in specific locations in order to collect sensorparameters, for example positioning an image sensor to record images ofthe door locking mechanism.

Optionally, the electro-mechanical mechanism allows moving sensor 210through a range of positions as appropriate for specific sensor. Forexample, a video sensor may be moved around all sides of container 213to record any external damage, and/or a hazardous materials sensor maybe moved along all hinges and/or around all openings to test the air forpresence of traces of hazardous materials.

Optionally, mount 211 is attachable to container lifting mechanism 212by mechanical and/or chemical attachment, for example a bolt that isdrilled into container lifting mechanism 212, a weld, a heat bond, anadhesive, and/or any other means of mechanical and/or chemicalattachment.

Optionally, Sensor 210 is attachable directly to container liftingmechanism 212 by mechanical and/or chemical attachment, as describedabove.

Reference is now made again to FIG. 1 . As shown in 101, process 100begins as container 213 is being moved by shipping container liftingmechanism 212. Process 100 may be executed for example by LUD 200.

As shown in 102, optionally the identification number (ID) of container213 is detected from characters printed on the exterior of container213, as described below. The ID may be an ISO 6346 conform containernumber, a serial number, and/or any other number and/or text used toidentify a container.

For example the ID may be detected by executing on LUD HW processor 221an optical character recognition (OCR) code and/or video contentanalysis (VCA) code located in Parameter Analyzer module 201 to extractand analyze an image from a sensor parameter collected by an imagesensor 213. Any other text on the exterior of container 213 may bedetected as described above. As used herein, the term image refers todigital still images and/or video images.

Optionally, the ID of container 213 may also be detected by a userinputting the ID via I/O 220.

Once the ID is detected, a query is performed to determine whether theID is present in a storage of records, for example by code instructionsin Parameter Analyzer module 201 executing on LUD HW processor 221 whichcompares the detected ID with the IDs stored in records in memory 208and/or the DBMS Module. The record may comprise the ID of container 213,sensor parameters, manifest parameters, and/or any other data associatedwith a container 213.

Optionally, manifest parameters that are printed on paper may beconverted to a sensor parameter, for example a paper bill of lading(BOL) may be scanned by an image sensor and/or a computer scanner, andmanifest parameters may be detected by OCR algorithm as described above.

Optionally, a plurality of records associated with a plurality ofcontainer IDs is received, for example from a network resource by I/O220 via network 230 and/or from a user via I/O 220, which stores thereceived records in storage 208 and/or the DBMS module.

Optionally, the records may comprise metadata. Metadata may comprise anelement of a signal output by sensor 213 as described above, for examplea time stamp of each parameter and/or an identification of the sensor.Metadata may be received from a computer file, for example to I/O 220via network 230 and/or from a user via I/O 220. Metadata may compriseidentification of originating container port and/or specific containerlifting unit, reports and/or alarms associated with container 213,identity of workers and/or managers who handled container 213,descriptions of any inspections performed, text entered by portpersonnel, digital images manually recorded by port personnel, asecurity category, mismatches between sensor and/or manifest parameters,and/or any other data associated with container 213.

Optionally, a user may change the detected ID and/or any other sensorparameter value in the record associated with container 213. Forexample, a user may detect via a display screen of I/O 220 that thedetected ID does not match the ID as it appears on the exterior ofcontainer 213, and may use a keyboard of I/O 220 to change the value ofthe detected ID in the record.

When the ID is detected, a request for manifest parameters associatedwith the ID is transmitted, as described below in 107.

As shown in 103, optionally when the ID of container 213 is notdetected, a new record is created and the ID of container 213 is addedto the created record, for example by code instructions from ParameterAnalyzer module 201 executing on LUD HW processor 221.

As shown in 104, optionally when the ID of container 213 is detected,the sensor parameters and/or manifest parameters associated withcontainer 213 ID are added to the existing record, for example by codeinstructions from Parameter Analyzer module 201 executing on LUD HWprocessor 221.

As shown in 105, optionally one or more sensors 210 captures one or moresensor parameters associated with container 213. As described above,sensor 210 may transmit the captured parameters as corresponding signalsvia network 230 to LUD HW Processor 221.

As shown in 106, optionally manifest parameters are received. Forexample, code instructions from Parameter Analyzer module 201 executingon LUD HW processor 221 may instruct transmitting a query requestingmanifest parameters for associated with container 213 ID via network 230to a Central Unit 500 and/or Port Unit 550 as described below in FIG. 5. The requested manifest parameters are received and stored in recordscorresponding to the appropriate ID, for example stored by I/O 220 instorage 108.

Manifest parameters may comprise any historical parameters associatedwith container 213, for example a shipment certificate, a shippingregistry, BOL, a seaward waybill, an electronic bill of lading (eB/L),shipping history, proof of ownership, an ID, a manifest of contents,identity of recipients, identity of senders, a shipping companyresponsible for delivering container 213 between any two points in theshipping history, metadata, historical data, and/or any other parametersdescriptive of container 213, the contents of container 213, and/or theshipping of container 213.

Optionally, prior to container 213 being lifted by container liftingmechanism 212, LUD HW Processor 221 may receive a notification that acontainer ID is scheduled to arrive in the future, and respond bytransmitting a request to network resources to receive manifestparameters, for example by code from Parameter Analyzer module 201executing on LUD HW processor 221. For example, LUD HW Processor 221 mayreceive input from I/O 220 that a specific container ID is scheduled toarrive in a week, and in response to this notification send a request,for example a Port Unit 550 and/or a Central Unit 500 as describedbelow, for manifest parameters associated with the specific containerID.

As shown in 107, optionally the sensor parameters and/or manifestparameters are analyzed, for example by code in Parameter Analyzermodule 201 executing on LUD HW processor 221. The analysis may compriseextracting images from parameters and detecting text from the image asdescribed above, comparing images extracted from parameters as describedbelow, detecting mismatches between values of parameters and expectedvalues as described below, and/or detecting mismatches between values ofparameters, as described above.

Optionally, expected values, ranges of values, thresholds, minimumvalues, and/or maximum values for sensor and/or manifest parameters maybe received, for example by input from a user via I/O 220 and/orreceived as a computer file via I/O 220.

When the value of the detected mismatch is greater than a user definedvalue, the mismatch may be an input to calculating a correlation, asdescribed below.

A mismatch may be detected between the value of a sensor parameter and auser defined expected value, for example between a value of a sensorparameter representative of the levels of hazardous materials ofcontainer 213 and a user defined maximum value.

A mismatch may be detected between the value of a manifest parameter anda user defined expected value, for example between a value of a manifestparameter representative of the weight of the container 213 and a userdefined maximum value.

Optionally, the analysis may comprise analyzing and/or comparing imagesof container 213, for example by code instructions for image processingand/or VCA in Parameter Analysis module 201 executing on LUD HWprocessor 221. An image extracted from a sensor parameter and an imageextracted from a manifest parameter may be compared, for example bycomparing images extracted from a sensor parameter image and acorresponding manifest parameter image of a seal, a door, and/or anyother component of container 213, a mismatch between the images may bedetected, indicating a possibility of tampering.

In a similar manner described above two or more images extracted fromtwo sensor parameter and an image extracted from manifest parameters maybe compare, and/or two or more images extracted from sensor parametersmay be compared.

As shown in 108, optionally security categories are calculated fromcorrelations between sensor parameters, manifest parameters, and/ordetected mismatches are calculated, for example by code instructions inClassifier Calculator module 203 executing on LUD HW processor 221.

Classifier Calculator module 203 may comprise code instructions forcalculating correlations by one or more member of a list of techniquescomprising statistical classification, correlation, linear regression,logistic regression, linear discriminant analysis, non-linearregression, and comparing an expected range of values with the mismatch.The output of the correlation calculation may be a report and/or asecurity category as described above.

For example, a user may input a classifier algorithm and/or securitycategories, for example via I/O 220 and/or received as a computer filevia I/O 220.

Optionally, the classifier algorithm may assign weights to differentinputs, for example a sensor parameter indicating a dangerously highlevel of radioactive material may have more influence on the securitycategory and/or reports than a mismatch between manifest and sensorparameter images indicating a possibility of tampering. The weights forinputs to the classifier algorithm may be input by user via I/O 220and/or via network 230 as described above.

Optionally, the security category is a type of report and/or alarm,where user input determines thresholds, recipients, triggers, and allother aspects of LUD 200 behaviors associated with reports, as describedbelow.

As shown in 109, a detected mismatch is transmitted, for example by codeinstructions in Reports Generator module 202 executing on LUD HWprocessor 221 instructing I/O 220 to transmit the mismatch to a specificuser defined network address, as described above.

Optionally, reports, security categories, and/or alarms are generatedand stored, for example in storage 208 and/or the DBMS module by codeinstructions in Reports Generator module 202 executing on LUD HWprocessor 221. Inputs to generate the alarms and/or reports may comprisethe security category, manifest and/or sensor parameters, detectedmismatches, user defined thresholds for mismatches, user defined reportsfor specific recipients, and/or user defined content for reports tospecific recipients.

For example, the following reports may be generated, where each reportis designated for a specific person, and the contents of the reportcomprises user defined relevant to that persons role regarding container213, as described above.

A report designated for a port worker may comprise container images,weight, dimensions, color, ID, and/or any detected mismatch(s)associated with container 213.

A report designated for a customs worker may comprise a list ofcontainer 213 contents according to customs categories, a record oftaxes and/or customs duties paid, all from manifest parameters.

A report designated for security personnel may comprise manifest and/orsensor parameters and/or specified detected mismatch(s), includingweight, size, color, and/or levels of radiation, hazardous materialsand/or explosives.

Alarm(s) may be generated according to user defined input, as describedabove.

An alarm may comprise a pre-recorded voice message delivered to adesignated phone number, a cell phone message such as a SMS, a messagedelivered to a wireless device such as a Smartphone, a message deliveredby an instant messaging program (IM) such as Gmail chat, a report, andthe like.

Optionally, an audible alarm and/or lighting mechanism may be activatedwhen user defined events occur. For example, LUD 200 may comprise asiren and/or strobe light. When a radioactive level is detected above auser defined threshold, the siren alarm and/or strobe light areautomatically turned on by code instructions in Reports Generator module202 executing on LUD HW processor 221.

Alarm(s) and/or report(s) may be transmitted to a user located outsidethe vicinity of LUD HW Processor 221, for example via network 230 to apublic and/or intranet network address.

Optionally, the generated reports, security categories, and/or alarmsmay be transmitted to designated recipients. For example, codeinstructions in Reports Transmitter module 204 executing on LUD HWprocessor 221 may copy reports and/or alarms from storage 208 and/or theDBMS module and present each alarm and/or report, together with acomputer network address for the designated recipient, to I/O 220 fortransmission on network 230.

Optionally, a subset of sensor and/or manifest parameters, detectedmismatches, alarms, and/or reports may be transmitted to a DBMS forstorage and/or future retrieval, for example to a Central Unit 500and/or a Port Unit 550 as described below.

Optionally, reports, security categories, and/or alarms may betransmitted to remote users. For example, reports and/or alarms may betransmitted via network 230 to the shipping company security officer whois located in a different country from LUD 200.

Reference is now made to FIG. 3 , a schematic illustration ofinformation flow between LUD 200, Central Unit 500, and Port Unit 550.Arrows in FIG. 3 represent flow of information.

As shown in 320, inputs for alarms, security categories, and/or reportsas described above in 109 are received and processed by LUD HW Processor221 as described above, and/or Port Unit 550 and/or Central Unit 500 asdescribed below. The following alarms may be generated, as describedabove in 109.

As shown in 322, an alarm may be generated when a mismatch is detectedbetween the locations of container 213 on two different dates. Forexample, when a container ID is detected as described above in 102 on acertain date, manifest parameters may be searched for previous locationsand date combinations, and the amount of elapsed time between eachlocation may be compared to a user defined table of travel time betweenthe locations. A mismatch may cause an alarm to be generated.

As shown in 323, an alarm may be generated when a specific combinationof mismatches are detected. For example, when two mismatches aredetected between manifest parameters and data derived from sensorparameters, an alarm may be generated. In this example, a singlemismatch would not cause an alarm to be generated.

As shown in 324, an alarm may be generated when a mismatch is detectedbetween a value of a sensor parameter and a value of a manifestparameter, for example between a value of a sensor parameterrepresenting the weight of container 213 and a value of a manifestparameter representing the weight of container 213. In this example, themanifest parameter originated from a BOL, but it may also originate froma seaward waybill, an electronic bill of lading (eB/L), and/or any othermanifest parameters of container 213.

As shown in 325, an alarm may be generated when a mismatch is detectedbetween a value of a sensor parameter and a user defined expected value,for example as described above in 107 when the value of a sensorparameter for the levels of hazardous materials of container 213 isgreater than a user defined maximum value.

As shown in 326, an alarm may be generated when a mismatch is detectedbetween a sensor parameter and a manifest parameter received from aDBMS, for example a DBMS in Central Unit 500 and/or Port Unit 550.

Reference is now made to FIG. 4 , a schematic illustration of anotherembodiment of LUD 200, according to some embodiments of the currentinvention. As shown in FIG. 4 , all lines with arrows representcommunications connections, for example as described in network 230above. Security officer 401, customs worker 402, port worker 403, and/orport supervisor 404 are all communications devices with a computernetwork address associated with the exemplary respective user.

As shown in 500, a subset of sensor and/or manifest parameters, detectedmismatches, alarms, security categories, and/or reports are transmittedto and/or received from Central Unit 500, as described below. As shownin 550, a subset of sensor and/or manifest parameters, detectedmismatches, alarms, security categories, and/or reports are transmittedto and/or received from Port Unit 550, as described below.

As shown in 412, visual and/or sound alarms are activated as describedabove. As shown in 413, reports and/or alarms are transmitted toexternal users, as described above.

Reference is now made to FIG. 5 , a schematic illustration ofconnections between Central Unit 500, Port Unit 550, and LUD 200,according to some embodiments of the current invention. Central Unit 500is adapted to collecting, storing, and/or transmitting parametersassociated with container 213 to and/or from a plurality of LUD 200. Theparameters may comprise sensor parameters, manifest parameters, detectedmismatch(s), security categories, and/or any other parameters associatedwith container 213.

As shown in FIG. 5 , all lines with arrows represent communicationsconnections, for example as described in network 230 above.

Central Unit 500 comprises one or more LUD HW processor 221 as describedabove, computer storage 208 as described above, and an I/O 220 asdescribed above. Code instructions software modules and for a DBMS arestored in storage 208, as described above. The DBMS code instructionswhen executing on LUD HW processor 221 are adapted to receive, store,and/or transmit sensor parameters associated with shipping containers213. Optionally, the DBMS code instructions when executing on LUD HWprocessor 221 is further adapted to receive, store, and/or transmitmanifest parameters, mismatches, reports, alarms, and/or any other dataassociated with container 213.

As shown in 450, Port Unit 450 is an instance of Central Unit 500 thatis located at a specific port, for example at the port of Hamburg or theport of Toulouse, and is connected to one or more LUD HW Processor 221located in a geographical proximity to the Port Unit 550, for examplewithin the respective port.

Optionally, some or all LUD 200 communicates with a Port Unit 550 vianetwork 230 as described above, which in turn communicates with aCentral Unit 500 via network 230 as described above.

Optionally, Port Unit 550 may request from Central Unit 500 manifestparameters associated with containers that are scheduled to arrive inthe future at the corresponding port, as described above in 107.

Optionally the DBMS of LUD 200, Port Unit 550, and Main Unit 500comprise instances of a distributed DBMS. Optionally, the entities LUD200, Port Unit 550, and/or Central Unit 500 each transmit one to theother records associated with containers 213, for example, in a databasereplication process of a DBMS as is known in the art, where portions ofthe database relevant to each entity are received by the entity, so thatmultiple copies of the records may be stored in multiple locations.

Optionally, sensor parameters received by Central Unit 500 may becategorized as manifest parameters once stored in a DBMS or any otherstorage system, for example by code instructions in Parameter Analyzermodule 201 executing on LUD HW processor 221.

Central Unit 500 may receive parameters associated with container 213from other instances of Central Unit 500, LUD 200, Port Unit 550, and/ornetwork resources.

Optionally, the quantity of sensor and/or manifest parameters stored inCentral Unit 500 may comprise big data, where the use of predictiveanalytics, user behavior analytics, and/or other advanced data analyticsmethods may be employed to analyze the data, for example by codeinstructions in Classifier Calculator module 203 and executing on LUD HWprocessor 221. For example, the analytic methods mentioned above may beemployed to detect trends over time in security hazards for a specificport and/or shipping company, a correlation between combinations ofports and/or shipping companies and a probability of a security hazard,a geographical area comprising multiple ports that have elevatedsecurity hazards, and the like.

Reference is now also made to FIG. 6 which is a schematic illustrationof a system for collecting, storing, and distributing parameters andmetadata associated with shipping containers and connected to externaltracking sources, according to some embodiments of the presentinvention. The numerals indicating objects are similar to the onedescribed above, however the system further connected to an externaltracking source 5500 that receives inputs from exemplary sources such ascameras, applications, scanners and/or the like. According to theseembodiments of the present invention, data collected from externaltracking sources such as one or more port unit(s) is correlated withdata originates from other one or more port unit(s) and/or externaltracking sources 5500 such as external systems for calculating ageographical transport route for each one of the containers. In suchembodiments, data regarding each container may be logged to and/orcoordinated in a global database, either centralized or distributed. Forexample the database may include a plurality of unique records, eachassociated with a different container identifier (e.g. set ofcharacters, a barcode image, etc.). The geographical transport route maybe maritime, aerial, territorial and/or a combination thereof. Thecurrent geographical transport route which is calculated per containermay be matched with an estimated geographical transport route given orcalculated for the container, for instance based on target address, BOLanalysis and/or the like.

Optimally, container(s) are identified by analyzing images capturedusing external tracking source 5500 which are connected or includevarious imaging systems which are geographically distributed in variousareas, optionally worldwide. For example, the images may be captured bytoll roads cameras (e.g. marked as cam), vehicle sensors, such as shipdeck sensors, a track carrier sensor, street cameras, paper bill oflading (BOL) scanners (e.g. marked as scan), and/or by cameras of mobiledevices executing an application facilitating users to upload images ofcontainers (e.g. marked as App). Other container detector schemes may bebased on readings of tag readers such as Bluetooth tag readers, NearField Communication (NFC) tag readers. As used herein, vehicle sensorssuch as track carrier sensor(s) or ship deck sensor(s) are sensorsmounted on vehicles for detecting a presence of a container. Forexample, the sensor may be an NFC tag reader, a camera, and/or a scannermounted on a container carrying vehicle such as a ship or track or aplane for detecting the identity of a container carried by therespective vehicle.

In use, images are analyzed to identify various container identifiers,such as container machine readable identifiers (e.g. a barcode, a QuickResponse (QR) code etc.). Then, the container identifier is used forsearching a record to update with container information, such aslocation, detected color, detected weight, detected status (e.g. open,closed, etc.) and/or the like. The logged data can then be analyzed todeduce a geographical route of each container, a current estimatedlocation of each container, a current status or change of status percontainer etc.

Optionally, the geographical route by a combination data from the LUDswith an external tracking source 5500 such as a Windward™ service or anyother maritime data platform that tracks the movement of shipsworldwide. In such embodiments, movement of a container may be estimatedor tracked by correlating between each container and ship(s) indicatedas carrying the container, for example in the respective BOL, andderiving the geographical route of the container from the route of theship(s).

In an exemplary case, a route of a container is deduced from analyzing aBOL captured on a first time frame, presence indications from 2different port units 550, a presence of the barcode of the container inan image captured by a tool road camera, a presence of the barcode ofthe container in an image captured by a street camera, and a reading ofan NFC tag in proximity to an NFC reader. In another exemplary case, aroute of a container is deduced from analyzing a presence indicationsfrom 2 different port units 550, an input of a track driver to adesignated application, either using a QR scanner or a manual input, apresence of the barcode of the container in images captured by differenttool road cameras and a presence of the barcode of the container in animage captured by a street camera.

In use, the calculated geographical route of each container may bematched with target address given to the container to detect or estimatemismatch and generate an alert accordingly. Additionally oralternatively in use, parameters extracted from images and/or othersensors may be matched with estimated parameters of each container, forexample estimated status, estimated weight or estimated color. Thisallows detecting irregularities automatically, for instance a change incolor, a premature opening of the container and/or the like. This alsoallows presenting an estimated current location based on the data whichis logged per container. This also allows identifying duplications ofcontainer identifiers and generates alerts accordingly (e.g. when thesame ID is detected in different locations or twice in the samelocation).

The system in FIG. 6 may be used for implementing a method forcorrelating between a geographic route of a container and a target routefor detecting irregularities as described above, for instance by thecentral unit 500. The method is based on receiving one or moregeographical target addresses given to a container (e.g. from ananalysis of the BOL), identifying port location(s) of the container inport(s) by analyzing port sensor output(s) of port sensor mounted oncontainer lifting mechanism(s) (e.g. the LUDs). This allows identifyingterrestrial location presence of the container by analyzing terrestrialsensor outputs of terrestrial sensors mounted to monitor a member of agroup consisting of a road, a street and storage. The terrestrial sensoroutputs may be images or video files of cameras as described above.Based on this information, a geographical route may be calculatedaccording to the port location(s) and terrestrial location(s) andirregularity(ies) can be detected based on an analysis of thegeographical route and the geographical target address. The method maybe combined with any of the above described systems and methods forfacilitating irregularity detection based on a combination of data fromthe LUDs and from external sources. Optionally the system may be usedfor providing a dashboard presenting indications each of a locationestimation of a container of a company or any other entity, for examplefor containers owned or associated with a certain company having aplurality of containers or load in a plurality of containers. As theabove system receives data about the location of containers at ports,ships, tracks and/or the like the estimated location of differentcontainers may be presented on a graphical user interface to anoperator. The display maybe as a dot on a route depicted on a map and/oras a log indicating the last location identified by the system. Thetracking is done both in the sea, in the air and/or on the ground.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

It is expected that during the life of a patent maturing from thisapplication many relevant sensors will be developed and the scope of theterm sensor is intended to include all such new technologies a priori.

As used herein the term “about” refers to ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”. This termencompasses the terms “consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “one or more compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments and/or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the invention may include a plurality of “optional”features unless such features conflict.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

What is claimed is:
 1. A system adapted to collect security parametersfrom a shipping container while a container lifting mechanism is liftingand moving said container, comprising: a mount adapted to attach atleast one sensor to a container lifting mechanism, wherein said at leastone sensor is adapted to capture at least one sensor parameterassociated with a shipping container while said container liftingmechanism lifts said shipping container; a network interface adapted toreceive over a network at least one manifest parameter associated withsaid shipping container and at least one remote location sensorparameter captured by at least one additional sensor other than said atleast one sensor at a location remote from a whereabouts of saidcontainer lifting mechanism, wherein said at least one remote locationsensor parameter comprising at least one value representing a physicalproperty of said shipping container during capturing thereof and beingassociated with said shipping container responsive to said at least oneadditional sensor capturing an identifier of said shipping container; atleast one hardware processor adapted to execute code for detecting anirregularity based on data deduced from an analysis of said at least onesensor parameter, said at least one manifest parameter and said at leastone value comprised in said at least one remote location sensorparameter, and outputting a signal indicative of said irregularity. 2.The system of claim 1, wherein said hardware processor is furtheradapted to execute code for correlating said irregularity with asecurity category, wherein said correlation is calculated by at leastone member of a list of techniques comprising statisticalclassification, correlation, linear regression, logistic regression,linear discriminant analysis, non-linear regression, and comparing anexpected range of values with said detected irregularity.
 3. The systemof claim 1, wherein said hardware processor is further adapted toexecute code for a database management system (DBMS) adapted to storingand instructing transmitting of at least one of said at least one sensorparameter and said at least one remote location sensor parameter.
 4. Thesystem of claim 1, wherein at least one of said at least one sensor andsaid at least one remote location sensor comprises at least one memberof a group consisting of weight sensors, length sensors, image sensors,barcode sensors, video recorders, gamma ray sensors, explosives sensors,radiation sensors, and hazardous material sensors, and wherein at leastone of said at least one sensor parameter and said at least one remotelocation sensor parameter comprises parameters captured by acorresponding said at least one member.
 5. The system of claim 1,wherein said analysis comprises at least one member of a list ofanalysis techniques comprising calculating at least one discrepancybetween a value of said at least one sensor parameter and an expectedrange of values, calculating at least one discrepancy between a value ofsaid at least one manifest parameter and an expected range of values,image processing, video content analysis (VCA), and optical characterrecognition (OCR).
 6. The system of claim 1, wherein said irregularitycomprises a discrepancy between said deduced data and said at least onemanifest parameter greater than an expected value.
 7. The system ofclaim 1, wherein said at least one manifest parameter comprises at leastone of a list of parameters associated with said shipping containerconsisting of a subset of said at least one sensor parameter, shippinghistory, owner of said container, an identification number, owner of acontents of said container, a manifest of contents, identity ofreceivers, identity of senders, a shipping company responsible fordelivery between any two points in said shipping history, and any otherparameters associated with said shipping container.
 8. The system ofclaim 1, wherein said hardware processor is further adapted to executecode for detecting a mismatch between data deduced from said analysis ofsaid at least one manifest parameter and said analysis of said at leastone sensor parameter.
 9. The system of claim 1, wherein said hardwareprocessor is further adapted to execute code for detecting a mismatchbetween data deduced from said analysis of a plurality of said at leastone manifest parameters.
 10. The system of claim 1, wherein saidhardware processor is further adapted to execute code for detecting amismatch between data deduced from said analysis of a plurality of saidat least one sensor parameters.
 11. The system of claim 1, wherein saidmount comprises a connecting arm wherein a distal end is attached tosaid at least one sensor, and a proximal end is attached to saidcontainer lifting mechanism.
 12. The system of claim 1, wherein saidmount provides at least one degree of freedom between said at least onesensor and said container lifting mechanism.
 13. The system of claim 1,wherein said mount comprises an electro-mechanical mechanism whichautomatically positions said sensor in proximity to at least one optimalposition for detecting at least one said sensor parameter.
 14. Thesystem of claim 1, wherein said mount automatically moves said sensorthrough a range of positions and orientations relative to said containerlifting mechanism.
 15. The system of claim 1, wherein said mount iscontrolled remotely by a user utilizing a controller interface.
 16. Asystem for collecting, storing, and distributing security parametersassociated with a shipping container comprising: at least one computingprocessor comprising: a network interface adapted to receive over anetwork at least one sensor parameter from at least one sensor mountedon at least one container lifting mechanism, at least one manifestparameter associated with said shipping container and at least oneremote location sensor parameter captured by at least one additionalsensor other than said at least one sensor at a location remote from awhereabouts of said container lifting mechanism, wherein said at leastone remote location sensor parameter comprising at least one valuerepresenting a physical property of said shipping container duringcapturing thereof and being associated with said shipping containerresponsive to said at least one additional sensor capturing anidentifier of said shipping container; at least one hardware processoradapted to execute code instructions, said code instructions comprisinga database management system (DBMS); and said DBMS adapted to receivequeries for data associated with said shipping container, and to respondwith at least one of said at least one sensor parameter and said atleast one value comprised in said at least one remote location sensorparameter.
 17. The system of claim 16, wherein at least one of said atleast one sensor and said at least one remote location sensor comprisesat least one member of a group consisting of weight sensors, lengthsensors, image sensors, barcode sensors, video recorders, gamma raysensors, explosives sensors, radiation sensors, and hazardous materialsensors, and wherein at least one of said at least one sensor parameterand said at least one remote location sensor parameter comprisesparameters captured by a corresponding said at least one member.
 18. Thesystem of claim 16, wherein said at least one manifest parametercomprises at least one of a list of parameters associated with saidshipping container consisting of a subset of said at least one sensorparameter, shipping history, owner of said container, an identificationnumber, owner of a contents of said container, a manifest of contents,identity of receivers, identity of senders, a shipping companyresponsible for delivery between any two points in said shippinghistory, and any other parameters associated with said shippingcontainer.
 19. The system of claim 16, further comprising codeinstruction for detecting an irregularity based on data deduced from ananalysis of said at least one sensor parameter, said at least onemanifest parameter and said at least one remote location sensorparameter.
 20. A method for collecting security parameters from ashipping container while a container lifting mechanism is lifting andmoving said container, comprising: mounting at least one sensor to acontainer lifting mechanism, wherein said at least one sensor is adaptedto capture at least one sensor parameter associated with a shippingcontainer while said container lifting mechanism lifts said shippingcontainer; receiving said at least one sensor parameter; receiving overa network at least one manifest parameter associated with said shippingcontainer and at least one remote location sensor parameter captured byat least one additional sensor other than said at least one sensor at alocation remote from a whereabouts of said container lifting mechanism,wherein said at least one remote location sensor parameter comprising atleast one value representing a physical property of said shippingcontainer during capturing thereof and being associated with saidshipping container responsive to said at least one additional sensorcapturing an identifier of said shipping container; detecting anirregularity based on data deduced from an analysis of said at least onesensor parameter, said at least one manifest parameter and said at leastone value comprised in said at least one remote location sensorparameter, and outputting a signal indicative of said irregularity.